Development of the larval zebrafish as a genetic model for the nicotine response.

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Development of the larval zebrafish as a genetic model for the nicotine response.

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2010-08

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Tobacco use is predicted to result in over 1 billion deaths worldwide by the end of the 21st century. How genetic variation contributes to the observed differential predisposition in the human population to drug dependence is unknown. The zebrafish (Danio rerio) is an emerging vertebrate model system for understanding the genetics of behavior. We developed a nicotine behavioral assay in zebrafish and applied it in a forward genetic screen using gene-breaking transposon mutagenesis. We used this method to molecularly characterize bdav/ cct8 and hbog/gabbr1.2 as mutations with altered nicotine response. Each have a single human ortholog, identifying two points for potential scientific, diagnostic, and drug development for nicotine biology and cessation therapeutics. We show this insertional method generates mutant alleles that are reversible through Cre-mediated recombination, representing a conditional mutation system for the zebrafish. Additionally, we developed a conditioned place preference assay for use with larval zebrafish. This assay allows for the perturbation of the differences in genetic function between the physiological and learned response representing one of the first associative learning based assays in the larval zebrafish. The combination of this reporter-tagged insertional mutagen approach and zebrafish provides a powerful platform for a rich array of questions amenable to genetic-based scientific inquiry, including the basis of behavior, epigenetics, plasticity, stress, memory, and learning.

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University of Minnesota Ph.D. dissertation. August 2010. Major: Comparative and Molecular Biosciences. Advisor: Stephen C. Ekker. 1 computer file (PDF); vii, 123 pages, appendices A-C. Ill. (some col.)

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Petzold, Andrew Michael. (2010). Development of the larval zebrafish as a genetic model for the nicotine response.. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/97849.

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